Abstract
The RECONTRA translator, a simple connectionist translator between natural languages, has been able to approach several simple MT tasks. In this paper we create a variant of the RECONTRA topology which takes into account what seems to be the natural work of the human brain in the translation process: complete paragraphs or sentences are translated, not individual words. Thus, the RECONTRA translator is modified to present as output several words at the same time. Experimentally, this simple modification has shown an improvement in the translation results.
Partially supported by the Generalitat Valenciana Project number GV/2007/105.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Koncar, N., Guthrie, G.: A Natural Language Translation Neural Network. In: Procs. of the Int. Conf. on New Methods in Language Processing, Manchester, pp. 71–77 (1994)
Waibel, A., Jain, A.N., McNair, A.E., Saito, H., Hauptmann, A.G., Tebelskis, J.: JANUS: A Speech-to-Speech Translation System using Connectionist and Symbolic Processing Strategies. In: Procs. of the International Conference on Acustic, Speech and Signal Processing, pp. 793–796 (1991)
Castaño, M.A.: Redes Neuronales Recurrentes para Inferencia Gramatical y Traducción Automática. Ph.D. dissertation, Universidad Politécnica de Valencia (1998)
Casañ, G.A., Castaño, M.A.: Distributed Representation of Vocabularies in the RECONTRA Neural Translator. In: Procs. of the 6th European Conference on Speech Communication and Technology, Budapest, vol. 6, pp. 2423–2426 (1999)
Casañ, G.A., Castaño, M.A.: Automatic Word Codification for the RECONTRA Connectionist Translator. In: Perales, F.J., Campilho, A.C., Pérez, N., Sanfeliu, A. (eds.) IbPRIA 2003. LNCS, vol. 2652, pp. 168–175. Springer, Heidelberg (2003)
Casañ, G.A., Castaño, M.A.: A New Approach to Codification for the RECONTRA Neural Translator. In: Procs. Ninth IASTED International Conference on Artifical Intelligence and Soft Computing, pp. 147–152 (2005)
Elman, J.L.: Finding Structure in Time. Cognitive Science 4(2), 279–311 (1990)
Wang, Y., Waibel, A.: Modeling with structures in statistical machine translation. In: Procs. of the 36th annual meeting on Association for Computational Linguistics, Canada, vol. 2, pp. 1357–1363 (1998)
Zens, R., Och, F.J., Ney, H.: Phrase-based statistical machine translation. In: Jarke, M., Koehler, J., Lakemeyer, G. (eds.) KI 2002. LNCS (LNAI), vol. 2479, pp. 18–32. Springer, Heidelberg (2002)
Andrés-Ferrer, J., Juan-Císcar, A.: A phrase-based hidden markov model approach to machine translation. In: Procs. New Approaches to Machine Translation, pp. 57–62 (2007)
Kuncheva, L.I.: Combining Pattern Classifiers. John Wiley & Sons, Chichester (2004)
Rumelhart, D.E., Hinton, G., Williams, R.: Learning Sequential Structure in Simple Recurrent Networks. In: Rumelhart, D.E., McClelland, J.L., PDP Research Group (eds.) Parallel distributed processing: Experiments in the microstructure of cognition, vol. 1. MIT Press, Cambridge (1981)
Marzal, A., Vidal, E.: Computation of Normalized Edit Distance and Applications. IEEE Transactions on Pattern Analysis and Machine Intelligence 9(15) (1993)
Hinton, G.E., McClelland, J.L., Rumelhart, D.E.: Distributed representations. In: Rumelhart, D.E., McClelland, J.L. (eds.) Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Foundations, vol. 1. MIT Press, Cambridge (1986)
Mozer, M.C., Smolensky, P.: Skeletonization: a Technique for Trimming the Fat from a Network via Relevance Assessment. In: Touretzky, D.S. (ed.) Advances in Neural Information Processing, vol. 1, pp. 177–185. Morgan Kaufmann, San Francisco (1990)
Möller, M.F.: A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning. Neural Networks 6, 525–533 (1993)
Amengual, J.C., Castaño, M.A., Castellanos, A., Llorens, D., Marzal, A., Prat, A., Vilar, J.M., Benedí, J.M., Casacuberta, F., Pastor, M., Vidal, E.: The Eutrans-I Spoken Language System. Machine Translation, vol. 15, pp. 75–102. Kluwer Academic Publishers, Dordrecht (2000)
Prat, F., Casacuberta, F., Castro, M.J.: Machine Translation with Grammar Association: Combining Neural Networks and Finite-State Models. In: Procs. The Second Workshop on Natural Language Processing and Neural Networks, Tokio, pp. 53–61 (2001)
Civera, J., Juan, A.: Mixtures of IBM Model 2. In: Proc. of EAMT 2006, pp. 159–167 (2006)
Andrés-Ferrer, J., García-Varea, I., Casacuberta, F.: Combining translation models in statistical machine translation. In: Procs. of The 11th Int. Conference on Theoretical and Methodological Issues in Machine Translation (TMI 2007), pp. 11–20 (2007)
Zell, A., et al.: SNNS: Stuttgart Neural Network Simulator. User manual, Version 4.1. Technical Report no. 6195, Institute for Parallel and Distributed High Performance Systems, Stuttgart: University of Stuttgart (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Casañ, G.A., Castaño, M.A. (2008). An Improved Connectionist Translator between Natural Languages. In: Geffner, H., Prada, R., Machado Alexandre, I., David, N. (eds) Advances in Artificial Intelligence – IBERAMIA 2008. IBERAMIA 2008. Lecture Notes in Computer Science(), vol 5290. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88309-8_29
Download citation
DOI: https://doi.org/10.1007/978-3-540-88309-8_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88308-1
Online ISBN: 978-3-540-88309-8
eBook Packages: Computer ScienceComputer Science (R0)